S’engager dans l’analyse discursive en cours de FLE : pour une linguistique citoyenne
Bibliographic record
Abstract
Le travail porte sur deux approches scientifiques du langage utilisées sous perspective didactique pour aider les étudiants du français dans la communication spécialisée à découvrir comment traiter le langage et essayer d’entrer, après tout, dans la dimension sémantique qui représente l’objectif principal de l’analyse du discours. D’un côté, l'École américaine aide à décrire la syntaxe. De l’autre côté, l'École française à comprendre la structure du discours. Nous essayons de montrer que les idées de Chomsky ne sont pas en contradiction avec celles de Culioli, mais que les deux sont complémentaires. De la même manière, chaque citoyen européen d’aujourd’hui devrait être capable de proposer une synthèse de deux idées qu'il confronterait. La citoyenneté européenne se montre donc précieuse.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.018 |
| Scholarly communication | 0.011 | 0.016 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".